And yet all that pales in comparison to using react (or whatever framework) over vanilla js. Enter McMaster-Carr.

Using bencode over json would probably speed up the web more. Not to mention good ole ASN.1 (well, at least some binary schemes for ASN.1). The web is completely cooked when it comes to efficiency.

I blame Bavaria. If Germany had multiple price zones like other European countries instead of one giant one prices would plummet here in the north, while they’d explode in Bavaria. The state that does not want wind power, does want nuclear power, but already knows ahead of time that its geology (with lots of mountains and granite) is unsuitable for nuclear waste storage. Meanwhile, north German wind power and Scandinavian hydro dams complement each other perfectly. The Bavarians could do the same with the Austrians, they just don’t. They want to eat cake and have it, too.

After reading through the abstract the article is pop sci bunk: They developed a method to save additional space with constant-time overhead.

Which is certainly novel and nice and all kinds of things but it’s just a tool in the toolbox, making things more optimal in theory says little about things being faster in practice because the theoretical cost models never match what real-world machines are actually doing. In algorithm classes we learn to analyse sorting algorithms by number of comparisons, and indeed the minimum necessary is O(n log n), in the real world, it’s numbers of cache invalidation that matters: CPUs can compare numbers basically instantly, getting the stuff you want to compare from memory to the CPU is where time is spent. It can very well be faster to make more comparisons if it means you get fewer, or more regular (so that the CPU can predict and pre-fetch), data transfers.

Consulting my crystal ball, I see this trickling down into at least the minds of people who develop the usual KV stores, database engineers, etc, maybe it’ll help maybe it won’t those things are already incredibly optimized. Never trust a data structure optimisation you didn’t benchmark. Never trust any optimisation you didn’t benchmark, actually. Do your benchmarks, you’re not smarter than reality. In case it does help, it’s going to trickle down into standard implementations of data structures languages ship with.

EDIT: I was looking an this paper, not this. It’s actually disproving a conjecture of Yao, who has a Turing prize, certainly a nice feather to have in your cap. It’s also way more into the theoretical weeds than I’m comfortable with. This may have applications, or this may go along the lines of the Karatsuba algorithm: Faster only if your data is astronomically large, for (most) real-world applications the constant overhead out-weighs the asymptotic speedup.

Cloud saves are for playing on more than one box as well as backup. Achievements, from the developer’s POV, give some insight into player behaviour, you can also drop hints there (I would never have tried to pet the manta in Satisfactory otherwise), make suggestions for tasks people can set themselves, etc. Whether you, as a player, cares honestly nobody but you gives a fuck.

I can tell you, for example, just from the achievement statistics, that a metric fuckton, an absolute majority, of Cities:Skylines players play modded. They do track city building milestones and very very few people are reaching anything even close to mid-game with achievements still enabled.

An MVP should not be a beta version, but fully functional and bug-free. The idea is to reduce scope to not necessarily even release it (though that’s possible) but to have a solid foundation onto which to duct-tape bells and whistles.

The MVP of a car doesn’t have heated seats, heck the seats might not even be adjustable without a wrench, but it’s absolutely going to drive and drive well and be crash-safe. Because if it doesn’t it’s nowhere close to being a viable car, go back and fix that before spending time on those seats.